Build smarter audio applications with a ResNet-inspired architecture, advanced data augmentation, and real-time inference pipelines.
Audiovis is a deep learning-powered framework for real-time sound classification. Using a ResNet-inspired CNN architecture, advanced data augmentation, and serverless GPU inference, Audiovis enables developers to build intelligent audio applications faster than ever.
Built for audio intelligence, optimized for developers.
Powerful residual blocks enable deep feature extraction for robust sound classification.
Mel spectrogram conversion transforms raw audio into images optimized for CNNs.
Visualize training metrics, confidence scores, and feature maps in real time.
Serverless GPU inference with blazing fast endpoints for production-ready AI apps.
'Audiovis transformed how I work with sound data. The feature map visualization is a game-changer.'
Sarah Johnson
AI Researcher
'Serverless GPU inference with Modal saved us weeks of deployment headaches. Lightning fast!'
David Kim
Full-Stack Developer
ResNet-inspired deep learning architecture
Mel Spectrogram audio preprocessing
Advanced augmentation with Mixup & masking
Interactive Next.js dashboard
FastAPI serverless inference
Real-time confidence scoring
Build, train, and deploy your own audio intelligence apps today.